With increased reliance on the operation of electronic equipment for day-to-day tasks, as well as the circuits and components within them, it is increasingly important to be able to assess not only the operating state of such equipment, but also if and when such equipment is experiencing degraded operation or is near failure and end of useful life. The ability to have Condition Based Maintenance (CBM) and Prognostic Health Management (PHM) capability on electronic systems, in order to monitor operating states, track performance, identify degraded performance and predict useful life is of significant advantage to the military as well as the commercial sector.
The electronic systems PHM technology begins by utilizing both diagnostic and prognostic features to develop health indicators to assess the current health and predict the amount of useful life remaining of an electronic system.
An electronic health indicator is a collection of one or more diagnostic features used to determine the overall lifetime (or health) of a system. An electronic health indicator is primarily used to determine the percentage of health remaining, or health index of a system.
A prognostic feature is a collection of one or more diagnostic features used to measure the rate of degradation to predict the amount of time left remaining during the useful life of the system, also referred to as Remaining Useful Life (RUL). One aspect of the present invention is the novel approach employed, particularly including the following: (i) No external circuit requirements; (ii) No circuit or system alterations; (iii) Data acquisition using low bandwidth connection; (iv) No external sensor requirements; and (v) Identification and verification of features (feature extraction) as trend indicators of damage accumulation.
Prognostic health management using minimal or no sensors is a further advantage as it avoids increasing costs and reduces the complexity of the equipment. Accordingly, aspects of the disclosed systems and methods are directed to the use of PHM techniques both at a general equipment level and also at the electronic system component and circuit level.
Use of existing electronic systems data (Circuit as a Sensor): The disclosed embodiments address the need for diagnostics and prognostics by providing a method to diagnose and predict electronic system failures and provide information supporting remaining useful life (RUL) assessment and prediction. This method incorporates existing data, typically utilized to perform a core or required device operation and not originally designed for failure prediction, to provide a self-contained system to detect faults and predict failures. As used herein, this is referred to as “circuit as sensor” (CAS). The circuit as sensor concept, enables implementation of prognostics for electronic devices, including devices having analog and/or digital components and in particular those that are digital and radio frequency in nature, utilizing few, if any, prognostics dedicated sensors. Examples of such devices would include, but are not limited to RF, IF, and baseband circuits, various digital circuits and motor drive applications and actuator controllers, as well as digital circuit error checking and flow control. This technology is presented using two use cases: a global positioning system (GPS) receiver and a RF transreceiver integrated circuit.
Use of available external measurements as condition indicators and degradation assessor: The approach integrates collaborative diagnostic and prognostic techniques from engineering disciplines including statistical reliability modeling, damage accumulation models, physics-of-failure modeling, signal processing and feature extraction, and automated reasoning algorithms. Further disclosed in embodiments herein is a PHM system for monitoring performance of an electronic system, comprising: a plurality of electronic circuit components (e.g., MOSFET), each component having a modeled operating state relative to at least one feature and each generating respective signals representative of the feature pursuant to the component operation; a data collection memory (e.g., RS-232 buffer, laptop) for storing samples of said electronic signals; and a computer (laptop), responsive to said electronic signals and the modeled operating state, for performing data analysis relative to the feature and detecting a variance in the operation of the component, wherein the computer further determines the health and/or remaining useful life of the component and the electronic system.
Performance assessment metrics derived from available external measurements: This method uses model-based assessments in the absence of fault indications, and updates the model-based assessments with sensed information when it becomes available to provide health state awareness at any point in time. Intelligent fusion of this diagnostic information with historical component reliability statistics provides a robust health state awareness as the basis for accurate prognostic predictions.
The following patents are believed to provide examples related to electronic prognostics and are hereby incorporated by reference, in their entirety, for their teachings:
7,034,660Sensor devices for structuralApr. 03, 2002health monitoring6,892,317Systems and methods for failureDec. 16, 1999prediction, diagnosis andremediation using dataacquisition and feedback for adistributed electronic system6,807,507Electrical over stress (EOS)Jun. 27, 2002monitor6,782,345Systems and methods forOct. 03, 2000diagnosing electronicsystems6,747,445Stress migration test struc-Oct. 31, 2001ture and method therefore6,745,151Remote diagnostics and prog-May 16, 2002nostics methods for complexsystems6,529,135Integrated electric motorOct. 12, 1999monitor6,363,332Method and apparatus for pre-Dec. 22, 1998dicting a fault conditionusing non-linear curvefitting techniques5,719,495Apparatus for semiconductorJun. 05, 1996device fabricationdiagnosis and prognosis5,270,222Method and apparatus forDec. 31, 1990semiconductor devicefabrication diagnosis andprognosis
The following papers also described the use of electronic prognostics and prognostic health management techniques and methods, and are hereby incorporated by reference in their entirety:    Brown, D. W.; Kalgren, P. W.; Byington, C. S.; Orsagh, R. F.; Electronic prognostics—A case study using Global Positioning System (GPS), Autotestcon 2005, IEEE Systems Readiness Technology Conference, September 2005;    Brown, D. W.; Kalgren, P. W.; Roemer M.; Dabney, T.; Electronic Prognostics a Case Study Using Switched Mode Power Supplies (SMPS), Autotestcon 2006, IEEE Systems Readiness Technology Conference, September 2006;    Ginart, A; Brown, D; Kalgren, P; and Roemer, M; On-line Ringing Characterization as a PHM Technique for Power Drives and Electrical Machinery, Autotestcon 2007, IEEE Systems Readiness Technology Conference, Baltimore's Inner Harbor, Baltimore Md., Sep. 17-20, 2007;    Kalgren, P.; Baybutt, M.; Minnella, C.; Ginart, A.; Roemer, M.; Dabney, T.; Application of Prognostic Health Management in Digital Electronic Systems, Big Sky, Mont., Mar. 3-10, 2007; and    Nanduri, S.; Almeida P.; Kalgren, P.; Roemer, M.; Circuit as a sensor, A practical approach toward embedded electronic prognostics, Autotestcon 2007, IEEE Systems Readiness Technology Conference, Baltimore's Inner Harbor, Baltimore Md., Sep. 17-20, 2007.
Disclosed in embodiments herein is a method for monitoring the health-state for electronic equipment, comprising: measuring current and voltage at an input and an output of the electronic equipment and acquiring data therefrom; using the measured data, calculating performance metrics for the equipment; separating the measured data into a plurality of data classes; generating performance models for at least one data class; extracting diagnostic features from measured data values by comparing calculated performance metrics with the diagnostic models; and identifying the source and severity of a fault based upon the diagnostic features.
Also disclosed in embodiments herein is a prognostic health management system for monitoring performance of an electronic system, comprising: a plurality of electronic circuit components, located in said electronic system, at least one component having a modeled operating state relative to at least one feature and generating respective electrical signals representative of the feature pursuant to the component operation; a data collection memory for storing samples of said electrical signals; and a computer processor, responsive to said electrical signals and the modeled operating state, for performing data analysis relative to the feature and detecting a variance in the operation of the component, wherein the processor further determines the health and/or remaining useful life of the component and the electronic system.